I have now finished my Research practise module and have found many sources of information relating to CCTV, although I am not sure how much of this information will still be relevant to Snapp now that I have changed my project in the direction of an advertising campaign.
1. code of practice http://www.ico.gov.uk/~/media/documents/library/data_protection/detailed_specialist_guides/ico_cctvfinal_2301.pdf
2. Data Protection act
3. The practiced retention period for images recorded on CCTV and London Underground
4. CCTV cameras can be ‘Networked’ via LAN/Wan/Internet allowing images to be viewed remotely on any PC
5. Highway Agency’s information line (HAIL)
6. Motion Detection
Jiwoong Bang; 19-22 Aug. 2012, “Motion Object and Regional Detection Method using Block-based background difference video frames,” Pages 350-357, Dept. of Computer Science, Dankook University, Yongin, South Korea. E:ISBN 978-0-7695-4824-1
7. MEDUSA, research programme underway in the UK, detection of guns as objects and people who then intend to commit gun crime.
Darker, I; 8-11 Oct. 2007, “Can CCTV reliably detect gun crime?” Pages 264-271, University of Loughborough, Print ISBN: 978-1-4244-1129-0
8. Face recognition systems
Ting Shan; 5-7 Sept. 2007, “Robust face recognition for intelligent CCTV based surveillance using one gallery image,” Pages 470-475, London. E-ISBN: 978-1-4244-1696-7
9. Blob tracking, (segmentation of object interior),
Sangkyu Kang, Joonki Paik, Andreas Koschan, Besma Abidi, Mongi A. Adibi, “Real-time video tracking using PTZ cameras,” Dept. of Electrical & Computer Engineering, University of Tennessee. Doi:10.1117/12.514945
10. Tracking of complex objects along with more complex object interaction like tracking objects moving behind obstruction
Black, James, Tim Ellis, Paul Rosin, 2003, “A novel method for Video Tracking Performance Evaluation.” Pages 125-132, Digital Imaging Research Centre, Kingston University, Surrey, Cite Seer X: 10.1.1.10.3365
11. Range of techniques to combat electronic hacking.
12. .gov site arguing against vandalism.
13. A system where a camera can be split up in to cells and some deactivated from motion detection.
14. Details of a system that incorporates many forms of facial recognition working together to reduce the number of false positives generated.
Lone,M.A., 7-9 Oct 2011, “Automatic Face Recognition System by combining four individual Algorithms,” Pages 222-226, Dept. Computer Science & Engineering, Baba Ghulam Shah Badshah University, Rajouri, India. Print ISBN: 978-1-4577-2033-8